By Topic

Algorithms for reducing the semantic gap in image retrieval systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Ion, A.L. ; Univ. of Craiova, Craiova

In this paper we study the possibilities to discover correlations between visual primitive characteristics and semantic concepts of images, meaning the extraction of semantic meaning based on learning, from an image database. The problem of automatic discovery of semantic inference rules is approached. A semantic rule is a combination of semantic indicator values, which are visual elements, that identifies semantic concepts of images. The annotation procedure starts with the semantic rules generation on each image category. The language used for rules representation is Prolog. The advantages of using Prolog are its flexibility and simplicity in representation of rules. Our methods are not limited to any specific domain and they can be applied in any field.

Published in:

Human System Interactions, 2009. HSI '09. 2nd Conference on

Date of Conference:

21-23 May 2009